Deep-Learning-Based Reconstruction of Single-Breath-Hold 3 mm HASTE Improves Abdominal Image Quality and Reduces Acquisition Time: A Quantitative Analysis.

IF 2.8 4区 医学 Q2 ONCOLOGY
Felix Kubicka, Qinxuan Tan, Tom Meyer, Dominik Nickel, Elisabeth Weiland, Moritz Wagner, Stephan Rodrigo Marticorena Garcia
{"title":"Deep-Learning-Based Reconstruction of Single-Breath-Hold 3 mm HASTE Improves Abdominal Image Quality and Reduces Acquisition Time: A Quantitative Analysis.","authors":"Felix Kubicka, Qinxuan Tan, Tom Meyer, Dominik Nickel, Elisabeth Weiland, Moritz Wagner, Stephan Rodrigo Marticorena Garcia","doi":"10.3390/curroncol32010030","DOIUrl":null,"url":null,"abstract":"<p><p><b>Purpose:</b> Breath-hold T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) magnetic resonance imaging (MRI) of the upper abdomen with a slice thickness below 5 mm suffers from high image noise and blurring. The purpose of this prospective study was to improve image quality and accelerate imaging acquisition by using single-breath-hold T2-weighted HASTE with deep learning (DL) reconstruction (DL-HASTE) with a 3 mm slice thickness. <b>Method:</b> MRI of the upper abdomen with DL-HASTE was performed in 35 participants (5 healthy volunteers and 30 patients) at 3 Tesla. In a subgroup of five healthy participants, signal-to-noise ratio (SNR) analysis was used after DL reconstruction to identify the smallest possible layer thickness (1, 2, 3, 4, 5 mm). DL-HASTE was acquired with a 3 mm slice thickness (DL-HASTE-3 mm) in 30 patients and compared with 5 mm DL-HASTE (DL-HASTE-5 mm) and with standard HASTE (standard-HASTE-5 mm). Image quality and motion artifacts were assessed quantitatively using Laplacian variance and semi-quantitatively by two radiologists using five-point Likert scales. <b>Results:</b> In the five healthy participants, DL-HASTE-3 mm was identified as the optimal slice (SNR 23.227 ± 3.901). Both DL-HASTE-3 mm and DL-HASTE-5 mm were assigned significantly higher overall image quality scores than standard-HASTE-5 mm (Laplacian variance, both <i>p</i> < 0.001; Likert scale, <i>p</i> < 0.001). Compared with DL-HASTE-5 mm (1.10 × 10<sup>-5</sup> ± 6.93 × 10<sup>-6</sup>), DL-HASTE-3 mm (1.56 × 10<sup>-5</sup> ± 8.69 × 10<sup>-6</sup>) provided a significantly higher SNR Laplacian variance (<i>p</i> < 0.001) and sharpness sub-scores for the intestinal tract, adrenal glands, and small anatomic structures (bile ducts, pancreatic ducts, and vessels; <i>p</i> < 0.05). Lesion detectability was rated excellent for both DL-HASTE-3 mm and DL-HASTE-5 mm (both: 5 [IQR4-5]) and was assigned higher scores than standard-HASTE-5 mm (4 [IQR4-5]; <i>p</i> < 0.001). DL-HASTE reduced the acquisition time by 63-69% compared with standard-HASTE-5 mm (<i>p</i> < 0.001). <b>Conclusions</b>: DL-HASTE is a robust abdominal MRI technique that improves image quality while at the same time reducing acquisition time compared with the routine clinical HASTE sequence. Using ultra-thin DL-HASTE-3 mm results in an even greater improvement with a similar SNR.</p>","PeriodicalId":11012,"journal":{"name":"Current oncology","volume":"32 1","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11763676/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/curroncol32010030","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose: Breath-hold T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) magnetic resonance imaging (MRI) of the upper abdomen with a slice thickness below 5 mm suffers from high image noise and blurring. The purpose of this prospective study was to improve image quality and accelerate imaging acquisition by using single-breath-hold T2-weighted HASTE with deep learning (DL) reconstruction (DL-HASTE) with a 3 mm slice thickness. Method: MRI of the upper abdomen with DL-HASTE was performed in 35 participants (5 healthy volunteers and 30 patients) at 3 Tesla. In a subgroup of five healthy participants, signal-to-noise ratio (SNR) analysis was used after DL reconstruction to identify the smallest possible layer thickness (1, 2, 3, 4, 5 mm). DL-HASTE was acquired with a 3 mm slice thickness (DL-HASTE-3 mm) in 30 patients and compared with 5 mm DL-HASTE (DL-HASTE-5 mm) and with standard HASTE (standard-HASTE-5 mm). Image quality and motion artifacts were assessed quantitatively using Laplacian variance and semi-quantitatively by two radiologists using five-point Likert scales. Results: In the five healthy participants, DL-HASTE-3 mm was identified as the optimal slice (SNR 23.227 ± 3.901). Both DL-HASTE-3 mm and DL-HASTE-5 mm were assigned significantly higher overall image quality scores than standard-HASTE-5 mm (Laplacian variance, both p < 0.001; Likert scale, p < 0.001). Compared with DL-HASTE-5 mm (1.10 × 10-5 ± 6.93 × 10-6), DL-HASTE-3 mm (1.56 × 10-5 ± 8.69 × 10-6) provided a significantly higher SNR Laplacian variance (p < 0.001) and sharpness sub-scores for the intestinal tract, adrenal glands, and small anatomic structures (bile ducts, pancreatic ducts, and vessels; p < 0.05). Lesion detectability was rated excellent for both DL-HASTE-3 mm and DL-HASTE-5 mm (both: 5 [IQR4-5]) and was assigned higher scores than standard-HASTE-5 mm (4 [IQR4-5]; p < 0.001). DL-HASTE reduced the acquisition time by 63-69% compared with standard-HASTE-5 mm (p < 0.001). Conclusions: DL-HASTE is a robust abdominal MRI technique that improves image quality while at the same time reducing acquisition time compared with the routine clinical HASTE sequence. Using ultra-thin DL-HASTE-3 mm results in an even greater improvement with a similar SNR.

求助全文
约1分钟内获得全文 求助全文
来源期刊
Current oncology
Current oncology ONCOLOGY-
CiteScore
3.30
自引率
7.70%
发文量
664
审稿时长
1 months
期刊介绍: Current Oncology is a peer-reviewed, Canadian-based and internationally respected journal. Current Oncology represents a multidisciplinary medium encompassing health care workers in the field of cancer therapy in Canada to report upon and to review progress in the management of this disease. We encourage submissions from all fields of cancer medicine, including radiation oncology, surgical oncology, medical oncology, pediatric oncology, pathology, and cancer rehabilitation and survivorship. Articles published in the journal typically contain information that is relevant directly to clinical oncology practice, and have clear potential for application to the current or future practice of cancer medicine.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信